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Issue 6, 2019
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Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

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Abstract

Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in Alzheimer's disease (AD). In this study, we constructed an AD-derived lncRNA-associated ceRNA network (LncACeNET) based on the ceRNA hypothesis and co-expressed correlation analysis of RNAs (miRNAs, mRNAs and lncRNAs) from AD patients. Based on this network, we preliminarily identified new potential AD biomarkers including hsa-miR-155-5p, CERS6-AS1, and CTB-89H12.4. The functional enrichment analysis demonstrated that these inferred biomarkers were significantly correlated with AD-related biological processes such as neuron projection development and neuron projection morphogenesis. Notably, lncRNA CTB-89H12.4 is significantly associated with “calcium ion-regulated exocytosis of neurotransmitter”, “chemical synaptic transmission”, “presynaptic membrane assembly”, “receptor localization to synapse”, and “learning”. This indicates the important role of CTB-89H12.4 as a promising target for AD therapy. Subsequently, we used the computational pipeline DTINet and discovered 19 lines of probable therapeutic relationships between FDA-approved drugs and CTB-89H12.4, which offered a new avenue to repurpose existing FDA-approved drugs for AD indication. Our study provides a new landscape for LncACeNET in AD, and will benefit mechanism study and new drug development for AD.

Graphical abstract: Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

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Supplementary files

Article information


Submitted
15 Aug 2019
Accepted
06 Nov 2019
First published
22 Nov 2019

Mol. Omics, 2019,15, 459-469
Article type
Research Article

Comprehensive analysis of the lncRNA-associated ceRNA network identifies neuroinflammation biomarkers for Alzheimer's disease

Y. Zhou, Z. Xu, Y. Yu, J. Cao, Y. Qiao, H. Qiao and G. Suo, Mol. Omics, 2019, 15, 459
DOI: 10.1039/C9MO00129H

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